Spectroscopic identification of bio-organisms utilizing resonance or near-resonance-Raman spectroscopy, described in U.S. Pat. No. 4,847,198, incorporated herein by reference, is a method through which biological organisms are identified from the highly structured emission spectra resonantly excited by illumination with Deep UltraViolet, ˜0.2-0.3 micron, (DUV) radiation. FIG. 1 illustrates the prior art system described in U.S. Pat. No. 4,847,198. A light source 12 comprises a laser 14, e.g. a Nd-Yag device, producing high energy light pulses at 1064 nm, 532 nm, 355 nm, and 266 nm; a dye laser 16, e.g. a Quanta-Ray PDL-2 which shifts pulse energies from Yag frequencies to lower energies; and a wavelength extender 18 that either doubles the dye laser output or mixes the dye-laser output or doubled dye laser output with an Nd-Yag fundamental to produce pulsed UV light at a wavelength between 350-216 nm. The output from the wavelength extender 18 strikes a split prism 20 which produces two beams. A first reference beam strikes a mirror and is reflected onto a photodiode 22. The output from the photodiode is transmitted to a Princeton Applied Research Model 162 Boxcar Averager 24. A Spex Datamate DMO1 microcomputer 26 controls the stepping motor (not illustrated) of a monochromator 40, for general data acquisition and disc storage of spectra. The second beam from the prism 20 strikes a mirror 28 which directs the beam to a sample 30 under investigation. The energy backscattered from the sample is collimated by a lens 32, condensed by an optically aligned lens 34 and focused by the lens 34 on an entrance slit of the monochromator 40. In this manner, a single wavelength in the UV or DUV range illuminates the sample and backscattered energy, i.e. resonance or near-resonance enhanced Raman scattering, or Raman scattering from a microorganism with a characteristic spectrum or “fingerprint”, is collected.
FIGS. 2a and b show the highly structured spectra of identifiable biological organisms resonantly excited by illumination of the sample to be examined with deep ultraviolet, ˜0.2-0.3 micron, (DUV) light. FIG. 2a shows spectra from Pseudomonas fluorescens (top), E. Coli (second from top), Bacillus subtilis (third from top), and Staphylococcus epidermidis (bottom) illuminated by a single DUV wavelength. The spectra contain a few large peaks. Prior-art authors attempted to use the locations of the large peaks for identification. We observe that the peaks have different shapes, that the spectra are very structured and visibly different for each organism observed. With proper analysis techniques, therefore, the entire spectrum can be used to make an identification. FIG. 2b shows spectra from B. megaterium spores illuminated at widely separated times by 4 different DUV wavelengths. Prior-art authors note that different illumination wavelengths produce major peaks at similar locations. We, however, observe that each individual illumination wavelength produces a spectrum that differs in features other than the major peak location, thus adding to the information that comprises the organism's signature. The spectra originate from resonant and near-resonant interactions of the illuminating DUV light with chemical bonds within and among nucleic and amino acids that constitute more than 50% (by dry weight) of the organism's mass. Hence, the spectra constitute a (partial) fingerprint of the organism. Because the light is in the DUV region the bond interaction is near-resonant, the Raman scattering is enhanced with signal-to-noise ratios of 103-104 being typical. In previous studies, spectra, with signal-to-noise sufficient for analysis, from as few as 20 organisms in a clean environment measured in 15 seconds have been demonstrated. Very importantly for biological measurements, interference from broad-band fluorescence in the DUV region of the spectrum where this method operates is virtually non-existent. The illuminating light need not damage the sample, allowing confirmation of positive readings through immediately repeated measurements by the same instrument. The sample can also be saved for forensic examination by other techniques at a later time. In addition, the spectra have been shown to contain information about the organism's stage of development and other information useful for assessing the threat posed by the organism.
This prior art technique has very limited ability to identify species. The ability to distinguish gram + from gram − bacteria has been demonstrated, but more specific identification has not been possible. Even this crude level of identification has been demonstrated in pure samples only, not when the substance of interest is present along with other substances. Excitation at a single wavelength may excite not just the substance of interest but also some or all of the other substances present, spectrally masking its signature and making it difficult to interpret the emitted spectra and to identify the substance of interest.
Other approaches have applied spectral data processing algorithms to data resulting from a single illumination wavelength of pure samples but have demonstrated only a limited capability to distinguish between spectral “fingerprints”, that is, the ability to identify a signature of a particular species, organism, or substance. None have been successful identifying an organism in the presence of other substances and/or organisms. Some require obtaining sets of training data and do not therefore lend themselves effectively to real time processing needs. Others exhibit limited ability to identify organisms due to the inherent limitations of their spectral data processing methodology.
Other current identification technologies, such as PCR, require a pre-enrichment step—i.e. a step in which the organism to be identified is grown for hours or days to provide the large number of organisms required for the identification method to be effective.
There is a need for a substance detector that can identify substances in the presence of other substances, to do so rapidly, and to do so with high sensitivity, and specificity, for example, identifying a minimal number of an organism in the presence of other organisms.